loadData.py

#!/usr/bin/env python
# -*- coding: utf-8 -*-

from __future__ import print_function

from database import *
from operator import itemgetter, attrgetter
import util
import os
import glob


def loadDetections(fn):
    """
        load detections from fn in the different formats
    """
    dets = []
    print ("loading ", fn)
    if os.path.splitext(fn)[1] == ".txt":
        dets = loadDetectionsPascalFormat(fn)

    elif os.path.splitext(fn)[1] == ".ramananmat":
        dets = loadDetectionsRamanan(fn)
    elif os.path.splitext(fn)[1] == ".shenmat":
        dets = loadDetectionsShen(fn)
    elif os.path.splitext(fn)[1] == ".mat":
        dets = loadDetectionsYann(fn)
    elif os.path.splitext(fn)[1] == ".csv":
        dets = loadDetectionsCSV(fn)
    else:
        print (fn)
        raise Exception("Detection file format not supported")
    return dets


def loadDetectionsYann(fn):
    f = util.loadmat(fn)
    det = []
    widths = []
    heights = []
    size = f['ids'].shape[0]
    bb = f['BB']
    for i in range(size):
        key = f['ids'][i][0][0].split('.')[0]
        conf = float(f['confidence'][i][0])
        if f.has_key("del"):
            if f["del"][i] == 1:
                continue
        x1 = float(bb[0][i])
        y1 = float(bb[1][i])
        x2 = float(bb[2][i])
        y2 = float(bb[3][i])
        det.append([key, conf, x1, y1, x2, y2])
    dets = sorted(det, key=itemgetter(1), reverse=True)
    return dets


def loadDetectionsShen(fn):
    f = util.loadmat(fn)
    det = []
    for idl, dd in enumerate(f["DetectionResults"]):
        for ff in dd[0][0]["faces"][0]:
            det.append([dd[0][0]["filename"][0][0].split(
                "\\")[-1].split(".")[0], ff[4], ff[0], ff[1], ff[0] + ff[2], ff[1] + ff[3]])
    dets = sorted(det, key=itemgetter(1), reverse=True)
    return det


def loadDetectionsCSV(fn):
    import csv
    f = open(fn, "rb")
    rd = csv.reader(f, delimiter=";")
    det = []
    rd.next()
    for idl, dd in enumerate(rd):
        det.append([dd[2].split(".")[0], 1, int(dd[7]), int(
            dd[8]), int(dd[7]) + int(dd[9]), int(dd[8]) + int(dd[10])])
    dets = sorted(det, key=itemgetter(1), reverse=True)
    return det


def loadDetectionsPascalFormat(f):
    ff = open(f)
    fdet = ff.readlines()
    det = []
    for idl, l in enumerate(fdet):
        dd = l.strip().split(" ")
        score = float(dd[1])
        dd[2] = float(dd[2])
        dd[3] = float(dd[3])
        dd[4] = float(dd[4])
        dd[5] = float(dd[5])
        w = float(dd[4]) - float(dd[2])
        h = float(dd[5]) - float(dd[3])
        det.append([dd[0].split('.')[0], score, dd[2], dd[3], dd[4], dd[5]])
    dets = sorted(det, key=itemgetter(1), reverse=True)
    return dets


def loadDetectionsRamanan(fn):
    f = util.loadmat(fn)
    ids = f['ids']
    scores = []
    if f.has_key('sc'):
        scores = f['sc']
    boxes = f['BB']
    n = len(ids)

    det = []
    for i in range(n):
        this_id = ids[i][0][0].split(".")[0]
        if not scores == []:
            this_score = scores[i][0]
        else:
            this_score = 1.0
        box = boxes[:, i]
        x1 = float(box[0])
        y1 = float(box[1])
        x2 = float(box[2])
        y2 = float(box[3])
        det.append([this_id, this_score, x1, y1, x2, y2])
        if 0:
            im = util.myimread(
                "/users/visics/mpederso/databases/afw/testimages/" + this_id + ".jpg")
            pylab.clf()
            pylab.imshow(im)
            util.box([y1, x1, y2, x2])
            pylab.draw()
            pylab.show()
            raw_input()
    dets = sorted(det, key=itemgetter(1), reverse=True)
    return dets